The restaurant industry is beginning to explore artificial intelligence (AI) as a tool to implement dynamic pricing strategies, potentially altering how menu prices are set based on demand, competition, and customer willingness to pay. Traditionally, prices for items such as a £20 steak remain fixed regardless of factors like time of day or day of the week. However, emerging technologies are offering restaurateurs the ability to adjust prices in a more granular and responsive manner.
One company, Piemetrics, provides a system where restaurant owners upload their menu and location information. The AI then analyzes nearby competitors and their pricing on similar dishes to identify potential revenue opportunities. The platform offers a range of suggested prices for each menu item, aiming to help restaurants optimize margins. Piemetrics claims its technology can reveal immediate profit growth by identifying underpriced items. Its clients include major groups like The Restaurant Group as well as independent establishments such as SOOM and Barge East in London.
Despite this promise, some industry experts remain skeptical about widespread adoption. Peter Backman, a restaurant sector analyst, suggests limited enthusiasm exists for AI-driven pricing among restaurant operators, noting that such models may not align well with customer expectations in dining settings.
In the United States, AI has seen notable application, with McDonald’s employing machine learning to guide pricing recommendations for its franchisees. Investigations revealed price variations for a Big Mac at company-owned outlets located a short distance apart in California. McDonald’s, however, clarifies that AI does not set prices automatically and franchisees retain final authority over price decisions. There is currently no evidence that this system is used by McDonald’s in the United Kingdom.
Other providers, such as Revenue Management Solutions (RMS), offer software that integrates sales data, loyalty information, labor costs, and competitor pricing to recommend menu prices tailored to individual restaurants. RMS’s technology, which serves over 150,000 locations worldwide, rates menu items based on profitability and enables managers to simulate the impact of price changes on sales before implementing adjustments directly to point-of-sale systems. RMS acknowledges the challenges of raising prices, emphasizing the delicate balance between maintaining customer satisfaction and preserving profit margins.
Major British restaurant and pub operators maintain cautious approaches to AI-driven pricing. Burger King UK, for example, denies that AI influences its menu pricing decisions, relying instead on human management while using technology to expedite price changes across outlets. Stonegate, the largest pub company in Britain, has increased the frequency of pricing updates through technology, allowing pub managers to raise prices during peak times such as popular football matches. This approach sparked controversy in 2023 when roughly 800 Stonegate pubs increased beer prices by about 20p during busy periods.
Industry observers note that dynamic pricing in restaurants faces unique challenges compared to sectors like airlines or hotels, where price variability is generally more accepted and less visible to consumers. In dining, customers can easily observe disparities in prices paid by others, potentially triggering perceptions of unfairness. Traditional pricing variations like happy hours remain more readily accepted because of their transparency.
Economists from the Bank of England have suggested that conventional peak and off-peak pricing models may give way to "market-responsive pricing," where algorithms adjust prices in real time based on demand, capacity, and competitor actions. Nonetheless, consumer attitudes, particularly among British diners, appear less favorable toward opaque AI-driven pricing models.
While there may be resistance to machine-controlled price setting in restaurants, dynamic pricing may be more readily adopted in delivery and takeaway services, where customers are more accepting of variable fees during high-demand periods. As dynamic pricing becomes more pervasive in industries such as hospitality—with hotel room prices fluctuating increasingly frequently—it is likely only a matter of time before AI-driven pricing becomes more common in the restaurant sector, despite lingering concerns over customer fairness and transparency.